California Department Of Transportation Research Articles

Assessing wayside traffic noise levels using long-term noise monitoring and available Department of Transportation traffic data - worst-case noise traffic conditions, effects of repaving, and methods for comparing traffic noise data sets

The availability of automated continuous traffic data from State Departments of Transportation (DOTs), such as the California Department of Transportation (Caltrans) Performance Measurement System (PeMS), provides increased opportunities for the analysis of highway noise. Traffic data that is free to access and downloadable via the internet can be matched with unattended long-term noise measurement data to provide large datasets for analysis, without requiring field staff to be continuously on site. A 2018 ICF/Caltrans paper documented how this approach was used on an operating freeway to determine the volume of traffic that results in the highest one-hour energy average traffic noise level. At the time of those measurements, the subject freeway had Portland cement concrete pavement. The freeway has since been repaved with an open-graded rubberized asphalt concrete pavement overlay. The current study uses new (2023) traffic noise measurements and PeMS data to investigate how worst-noise conditions have changed and the effect of the repaving on wayside noise levels. Changes in traffic patterns since 2018 required the authors to normalize the measurement data for comparison. Opportunities were identified to take advantage of the large measurement data sets to match before-and-after data, and those methods are also described in this paper.

Regulating unproductive contract adaptation: A payment deduction mechanism

AbstractTo the best of our knowledge, our paper offers a first attempt to uncover a payment deduction mechanism for regulating unproductive contract adaptation. Our model uncovers that the payment deduction mechanism can expropriate the ex post unproductive profit of a contractor. Using the data from California Department of Transportation, we confirm the positive effect of ex post payment deduction on ex post unproductive profit. Our estimates are robust to different estimation methods with different types of standard errors and the potential endogeneity bias. The payment deduction mechanism offers general applications to constrain ineffective contract implementation in the infrastructure industry.

Brief history of lean in the public sector

The development of Lean principles within the public sector began in 2003 following Lean Construction Institute´s developing efforts on relational contracting. Later, challenges and opportunities for implementing Lean were identified in Californian construction law. Collaborations with entities like the California Department of Transportation and the University of California San Francisco showcased Lean's benefits, leading to legislative changes allowing broader implementation across the University of California system. Healthcare also saw streamlined processes through collaborations, in this case, between the P2SL, the Office of Statewide Health Planning and Development, and major healthcare companies, reducing project durations significantly. International expansion in 2009 led to successful Lean pilot projects in Germany and Finland. Inspired by Washington State's Lean governance practices, Lean in Public Sector Construction (LIPS) expanded its focus beyond construction. LIPS has conducted impactful global conferences, highlighting Lean's transformative role in reshaping diverse public sector operations and governance worldwide.

ANN-based estimation model for the preconstruction cost of pavement rehabilitation projects

To combat prevalent roadway aging, the California Department of Transportation (Caltrans) implements routine rehabilitation projects, which require cost estimation models for better management. Several models have been developed to estimate the construction costs of new highway projects; however, few have targeted the cost of pavement rehabilitation, and, of these, most have focused primarily on the construction phase. This study presents an artificial neural network (ANN) estimation model that predicts the cost of the preconstruction phases (predesign, design, and bidding) of pavement rehabilitation projects. The model was developed using 139 projects maintained by Caltrans over the past five years. Pareto principle and sensitivity analysis were used to identify five project items that contributed significantly to the model’s high estimation performance, which was demonstrated by a coefficient of multiple determination value (R 2) of 76.9%. Thus, the proposed model will allow Caltrans to properly estimate its budget and manage its performance during the preconstruction phases of pavement rehabilitation projects. Moreover, it overcomes many limitations of conventional preconstruction cost estimation models and will allow Caltrans to better manage up to $80B that may be spent on its preconstruction activities. Finally, the model provides a benchmarking tool for tracking and controlling expenses.

Noise Performance of Chip Seal Pavements

Increasing numbers of local and state highway agencies are using chip seals for highway pavement maintenance owing to their relatively low cost and simplicity of application. These surfaces can significantly increase both exterior traffic noise levels and interior noise for vehicle occupants. Recent studies included as part of the NCHRP 15-68 Effect Low Noise Rumble Strips Project have quantified these effects using pass-by and interior noise and on-board sound intensity (OBSI) measurements in several states. To minimize the tire–pavement noise generated by chip seals, the California Department of Transportation (Caltrans) has conducted research on different chip seal pavement designs near the City of Bishop, California. Previous measurements of chip seal pavement have indicated an average OBSI level of 106.2 dBA with a range of ±2 dB. The five quietest test sections at Bishop produced an average level of 101.8 dB with a range of ±0.6 dB. In this paper, previous pass-by and interior noise and OBSI measurements are provided along with the comparison of OBSI data to that measured at the Bishop sites. The performance and design information on the Bishop sites are also provided.

An application of Next Generation Concrete Surface texture to an existing concrete pavement

Between 2011 and 2013, the California Department of Transportation (Caltrans) installed New Generation Concrete Surface (NGCS) along a stretch of State Route 113 (SR 113). In the fall of 2013, this pavement was evaluated using the on-board sound intensity (OBSI) testing method. NGCS is a flush ground and grooved surface developed at Purdue University's Herrick Laboratory in 2004. This innovative, low noise grinding texture has minimal positive texture with good microtexture, which was intended to reduce noise levels at low frequencies, and has great macrotexture, which was intended to reduce noise levels at high frequencies. To evaluate the acoustic longevity of the pavement, OBSI testing was again completed in early 2023, and the long-term results are discussed in this paper. Additionally, the acoustic longevity of the NGCS pavement is compared to the long-term OBSI results collected between 2003 and 2010 on a ground concrete surface installed along Mojave SR 58. In 2022, NGCS was applied on a section of the U.S. 101 Freeway in Carpinteria in Southern California. The results of these measurements and the noise reductions achieved are also presented.

Noise and Pavement Rehabilitation Using Chip Seal Surfaces

In the United States, increasing number of local and state highway agencies are using chip seals for highway pavement rehabilitation due to their relatively low cost and simplicity of application. These surfaces can significantly increase both exterior traffic noise levels and interior noise for vehicle occupants. Recent studies have quantified these effects using pass-by and interior noise and on-board sound intensity (OBSI) measurements. In order to minimize these effects, the California Department of Transportation (Caltrans) has conducted research on different chip seal pavement designs near the City of Bishop, California. Previous measurements of chip seal pavement have indicated an average OBSI level of 106.2 dBA with a range of ±2 dB. The five quietest test sections at Bishop produced an average level of 101.8 dB with a range of ±0.6 dB. In this presentation, the previous pass-by and interior noise and OBSI measurements are provided along with the comparison of OBSI data to that measured at the Bishop sites. The performance and design information on the Bishop sites are also provided.

Large-scale evaluation of pavement performance models utilizing automated pavement condition survey data

Pavement performance models are an essential component of a pavement management system (PMS) and have a direct impact on future pavement condition prediction, selection of pavement maintenance and rehabilitation (M&R) methods, and budget planning and allocations. Therefore, it is critical to develop and maintain pavement performance models as accurate as possible. The California Department of Transportation (Caltrans) has implemented a modern pavement management system called PaveM. To maintain the intended functions of PaveM, regular updates of its databases and key components are necessary, including pavement performance models. This paper aims to evaluate the network-level pavement performance models in PaveM by utilizing the concept of deterioration rate and the most recent automated pavement condition survey (APCS) data. First, the concept of pavement deterioration rate was defined. The actual deterioration rates were calculated using two latest cycles of APCS data and then compared to the predicted deterioration rates obtained using APCS data and the current configurations of PaveM. Two typical pavement distresses (International Roughness Index and Caltrans’ asphalt pavement alligator B cracking) for one selected pavement treatment (thin overlay) were predicted using PaveM and compared to the actual APCS measurements. The results from this study show that the concept of deterioration rate was effective in evaluating the overall quality of performance models in PaveM as well as identifying the time spans in which the models may over- or under-predict pavement performance.

Optimization of prestressed concrete bridge girder section using a modified harmony search algorithm

Precast I girders provide rapid construction and structural simplicity, making them an increasingly popular choice for bridge construction. The current standard sections adopted by the American Association of State Highway and Transportation Officials (AASHTO) are not SI friendly and may be improved utilizing increasingly efficient metaheuristic optimization algorithms. Thus, this research study aims to obtain the optimum shape of Precast I (PCI) bridge girders commonly used in bridge construction due to various advantages. The optimization problem is solved using a modified metaheuristic optimization algorithm considering a number of constraints that are stipulated by the AASHTO LRFD code requirements. To show the capabilities of the utilized modified optimization algorithm, a comparison is performed with its baseline counterpart. The structural design optimization of bridge superstructures is performed with the objective of minimizing the total cost of the resulting superstructure. Consequently, the most economical shape of the PCI girders is obtained. The results of this analysis are then compared AASHTO and the California Department of Transportation (Caltrans) PCI girders. The new I girder sections exhibits 13–17% and 5–16% better structural efficiency factor (ρ) as well as 14–19% and 4–21% structural efficiency ratio (α) than Caltrans and AASHTO girders, respectively.Thus, new sections for PCI girders are developed having various heights to facilitate more economical design of bridges having various geometric properties such as span length, girder spacing and slab thickness.

Analysis of Constructability Practices in State Departments of Transportation under Organizational Constraints

Designers typically do not base critical design decisions on construction requirements and constraints, and soon realize that their designs could be difficult to build and expensive. Thus, construction expertise needs to be incorporated in the design process through applying constructability concepts at early project stages. With the underlying concept of a construction-driven design, there are many approaches used by transportation agencies in conducting constructability reviews (CRs), but the key is to develop an approach that is consistent and scalable to different ranges of environmental constraints and project delivery methods, while accounting for organizational structure. The objective of this paper is thus to investigate and recommend effective practices in CRs that could be used by Departments of Transportation (DOTs), given their organizational constraints. To achieve this objective, the methodology was divided into two major steps starting with a comprehensive literature review, followed by two case studies of DOTs employing two different constructability programs that align with their organizational policies and constraints: California Department of Transportation and Utah Department of Transportation. Results of the case studies highlight the common themes in their CRs (early involvement of the DOT construction team), whereas the organizational constraints also result in significant differences (CR formality level, and consultants’ and contractors’ involvement). This study thus highlights that there is no one-size-fits-all constructability approach and provides evidence and recommendations, through two different but successful CR processes, on the importance of developing a CR process that aligns with organizational constraints.

Empirical-Markovian approach for estimating the flexible pavement structural capacity: Caltrans method as a case study

An Empirical-Markovian approach is proposed to estimate the pavement structural capacity as a function of key stochastic and design parameters. The key stochastic parameters are the initial and terminal deterioration transition probabilities typically estimated from pavement distress records. These two transition probabilities have a major impact on the pavement performance trend predicted using Markovian processes. In addition, typical pavement design factors are included as related to traffic loadings, materials properties, and climate conditions. In particular, two distinct Empirical-Markovian models are developed to estimate the pavement structural capacity in terms of relative strength indicators such as the structural number (SN) and gravel equivalent (GE). The first model can estimate the structural capacity based on the initial transition probability and relevant design parameters, while the second one deploys the terminal transition probability along with other design parameters. The recommendation is to use the higher of the two structural capacity values estimated for a particular pavement project. The sample models presented based on the California Department of Transportation (Caltrans) design method have resulted in good model fittings as demonstrated by the various deployed statistics and error analysis, thus indicating the usefulness of the proposed Empirical-Markovian approach in estimating the pavement structural capacity for rehabilitation and design purposes. The model exponents can be obtained from solving a linear system of equations using data from a small project sample or solving a multi-variable linear regression model when a large road sample is available. The latter case provided sample generalized models with statistics indicating their high significance.

Effects of driving conditions on secondary aerosol formation from a GDI vehicle using an oxidation flow reactor

A comprehensive study on the effects of photochemical aging on exhaust emissions from a vehicle equipped with a gasoline direct injection engine when operated over seven different driving cycles was assessed using an oxidation flow reactor. Both primary emissions and secondary aerosol production were measured over the Federal Test Procedure (FTP), LA92, New European Driving Cycle (NEDC), US06, and the Highway Fuel Economy Test (HWFET), as well as over two real-world cycles developed by the California Department of Transportation (Caltrans) mimicking typical highway driving conditions. We showed that the emissions of primary particles were largely depended on cold-start conditions and acceleration events. Secondary organic aerosol (SOA) formation also exhibited strong dependence on the cold-start cycles and correlated well with SOA precursor emissions (i.e., non-methane hydrocarbons, NMHC) during both cold-start and hot-start cycles (correlation coefficients 0.95–0.99), with overall emissions of ∼68–94 mg SOA per g NMHC. SOA formation significantly dropped during the hot-running phases of the cycles, with simultaneous increases in nitrate and ammonium formation as a result of the higher nitrogen oxide (NOx) and ammonia emissions. Our findings suggest that more SOA will be produced during congested, slow speed, and braking events in highways.

Selective Entry in Highway Procurement Auctions

When participating in an auction is costly, a potential bidder has to decide whether to enter the auction or not. The extent to which the potential bidders know their private cost before making their entry decisions determines how selective the entry process is. Endogenous selective entry is common in many auctions and it has important implications for designing auctions, in particular, choosing the bid discount policy that is frequently used in public procurements to achieve distributional goals of the government. Prior empirical studies of the bid preferences were based on frameworks that either did not explicitly model endogenous participation or assumed endogenous, but non-selective participation. This study empirically investigated whether the entry process is selective in the highway procurement auctions run by the California Department of Transportation. To this end, the asymmetric affiliated-signal model was adapted to permit endogenous selective entry. Model parameters, including entry costs and distributions of construction costs for regular and fringe companies, were estimated nonparametrically. The results show evidence favoring selective entry of the fringe firms and imply that the level of bid discount required to achieve the procurement buyer’s policy objective may be lower than what is previously found in the literature under the assumption of non-selective entry.

Survivability of a Tesla collision into a non-operational crash attenuator in Mountain View, CA

Objective On March 23, 2018 a Tesla Model X driver was killed in Mountain View, CA after colliding with a previously collapsed crash attenuator at a speed of 31.7 m/s (70.8 mph). The attenuator, which must be repaired following a collision, had been struck 11 days prior by a 2010 Toyota Prius at a minimum speed of 33.9 m/s (75.8 mph). The Toyota driver survived. The maintenance of traffic safety hardware and benefit of the crash attenuator are evaluated. Methods Public information from an NTSB investigation is used to evaluate crash impact severity. Vehicle crash data from Event Data Recorders (EDRs) are compared with test data for the SCI Smart Cushion 100GM crash attenuator. An idealized triangular crash pulse is used to estimate longitudinal peak impact acceleration, and longitudinal impact energy is calculated. The medical outcomes for drivers are considered. Results The California Department of Transportation (Caltrans) maintenance and repair program for safety critical traffic safety hardware was found to be ineffective. The Tesla collision into the nonfunctional attenuator was estimated have roughly three times the impact force to the passenger compartment as it would have been if striking a functional attenuator. Conclusions The Tesla driver could have survived the collision had the crash attenuator been functional. Roadway management and timely maintenance of safety critical traffic hardware are necessary to ensure safety.

Assessment of California’s Continuously Reinforced Concrete Pavement Practice and Performance

Around 2009, the California Department of Transportation (Caltrans) adopted continuously reinforced concrete pavement (CRCP) as the preferred pavement type for high-volume truck corridors across the state. Over the last decade, Caltrans has constructed more than a dozen CRCP projects in different climates and exposure to different truck volumes. Caltrans was interested in assessing early CRCP performance and identifying potential areas where design, materials, plans, and specifications, and/or construction practices warranted improvement. This project included a review of national CRCP practice, documentation of Caltrans’ statewide practice, and condition assessment of select CRCP projects statewide. For the most part, Caltrans’ CRCP practice is similar to national guidance and other state highway agency practice. A condition assessment of 14 CRCP projects revealed a wide range of performance with various degrees of distresses (i.e., transverse, cluster, and Y-cracking, and punchouts). However, pavements with average transverse crack spacing below Caltrans’ desired lower limit of 3 ft appeared to have acceptable performance. Excessive map cracking, a high percentage of cluster cracking, and initial development of punchouts was evident in sections that appeared to be performing poorly. General recommendations are provided to advance Caltrans’ CRCP practice.

Fatigue and Fracture Properties of Asphalt Mixes Containing Low Content of Crumb-Rubber Modifier

AbstractThe California Department of Transportation has proposed to add a low amount of crumb-rubber modifier into dense-graded asphalt mixes, in addition to current policies of using gap- and open...

On Training Traffic Predictors via Broad Learning Structures: A Benchmark Study

A fast architecture for real-time (i.e., minute-based) training of a traffic predictor is studied, based on the so-called broad learning system (BLS) paradigm. The study uses various traffic datasets by the California Department of Transportation, and employs a variety of standard algorithms (LASSO regression, shallow and deep neural networks, stacked autoencoders, convolutional, and recurrent neural networks) for comparison purposes: all algorithms are implemented in MATLAB on the same computing platform. The study demonstrates a BLS training process two-three orders of magnitude faster (tens of seconds against tens-hundreds of thousands of seconds), allowing unprecedented real-time capabilities. Additional comparisons with the extreme learning machine architecture, a learning algorithm sharing some features with BLS, confirm the fast training of least-square training as compared to gradient training.

Data-driven analysis and forecasting of highway traffic dynamics

The unpredictable elements involved in a vehicular traffic system, like human interaction and weather, lead to a very complicated, high-dimensional, nonlinear dynamical system. Therefore, it is difficult to develop a mathematical or artificial intelligence model that describes the time evolution of traffic systems. All the while, the ever-increasing demands on transportation systems has left traffic agencies in dire need of a robust method for analyzing and forecasting traffic. Here we demonstrate how the Koopman mode decomposition can offer a model-free, data-driven approach for analyzing and forecasting traffic dynamics. By obtaining a decomposition of data sets collected by the Federal Highway Administration and the California Department of Transportation, we are able to reconstruct observed data, distinguish any growing or decaying patterns, and obtain a hierarchy of previously identified and never before identified spatiotemporal patterns. Furthermore, it is demonstrated how this methodology can be utilized to forecast highway network conditions.

Highway Art Policy Revisited: Rethinking Transfers of Copyright Ownership in State-Owned Transportation Artwork

In 2016, the California Department of Transportation (Caltrans) revised its policy standards with respect to the intellectual property rights of artists who create works of public art installed within the state highway system. While Caltrans had previously allowed artists to keep their copyrights subject to a nonexclusive license of certain reproduction rights to the state, the 2016 policy (the “Transportation Art Policy”) requires artists to assign their “entire rights, title and interest in” such works of art to Caltrans, including their “common law and federal copyright ownership rights.” The artist must execute a copyright assignment and transfer agreement, which Caltrans must approve, before the art is installed. This requirement exists even though the policy assumes that certain local “public agencies,” not the state of California itself, will be responsible for commissioning works of art; the policy directs the commissioning agency for a given work of art to also sign onto the assignment and transfer agreement.This Note argues that state policies that, like Caltrans’, require a transfer of copyright in works of public art are ill-fitted to their purposes, and that the goals of copyright law are better served by alternative contractual arrangements. In Part I, I provide an overview of the legal landscape in the United States with respect to transfers of copyright ownership, visual artists’ moral rights, and public art commissions. In Part II, I outline the substance of Caltrans’ Transportation Art Policy and the possible justifications for its 2016 revision, and then show why the policy is both a poor fit for those presumptive objectives and an unwarranted burden on stakeholders. Finally, in Part III, I discuss alternatives to public art policies that require copyright transfer. I argue that states or state agencies seeking to own public artwork should, as Caltrans once did, allow artists to retain copyright provided that they grant the state a nonexclusive license for reasonable public uses. The advantage of such an approach—which many other states already employ—is that it offers reasonable protection for the state’s legitimate interests in avoiding liability and enforcing the copyright, without the attendant harms to artistic creativity and to the public.

Findings from the California Vehicle Inventory and Use Survey

This paper describes the findings from the California Vehicle Inventory and Use Survey (CA-VIUS) which was administered between June 2016 and January 2018 and obtained data from a total of 11,118 fleets and 14,790 trucks. The surveys were segmented by registration, geography, vehicle type, and vehicle age, and the data collection effort exceeded sampling targets across almost all segments. The CA-VIUS is the largest statewide commercial vehicle data collection effort in the United States and will replace the 2002 National VIUS in transportation planning and emissions studies throughout California. Currently, the wealth of information provided by the survey is supporting the development of the California Statewide Freight Forecasting Model which is a fine-grained behavioral freight model. This model will allow California Department of Transportation and its partners to make more informed infrastructure and operational investment decisions. The CA-VIUS data will also be useful for researchers and practitioners hoping to understand the impacts and benefits of commercial vehicle movements on air quality, economic activity, safety, and vehicle usage. This paper documents key sampling and survey approaches, but mainly focuses on the key findings observed in the survey. This is a practical paper geared towards practitioners who are seeking to analyze a new VIUS survey and those who wish to implement one of their own.